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Range‐Based Estimation of Stochastic Volatility Models
Author(s) -
Alizadeh Sassan,
Brandt Michael W.,
Diebold Francis X.
Publication year - 2002
Publication title -
the journal of finance
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.151
H-Index - 299
eISSN - 1540-6261
pISSN - 0022-1082
DOI - 10.1111/1540-6261.00454
Subject(s) - stochastic volatility , volatility (finance) , econometrics , forward volatility , financial models with long tailed distributions and volatility clustering , range (aeronautics) , estimation , implied volatility , economics , gaussian , sabr volatility model , mathematics , physics , engineering , management , quantum mechanics , aerospace engineering
We propose using the price range in the estimation of stochastic volatility models. We show theoretically, numerically, and empirically that range‐based volatility proxies are not only highly efficient, but also approximately Gaussian and robust to microstructure noise. Hence range‐based Gaussian quasi‐maximum likelihood estimation produces highly efficient estimates of stochastic volatility models and extractions of latent volatility. We use our method to examine the dynamics of daily exchange rate volatility and find the evidence points strongly toward two‐factor models with one highly persistent factor and one quickly mean‐reverting factor.